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        Package&nbsp;trunk ::
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        <a href="trunk.BIP.SDE.gillespie-module.html">Module&nbsp;gillespie</a> ::
        Class&nbsp;Model
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<h1 class="epydoc">Class Model</h1><p class="nomargin-top"><span class="codelink"><a href="trunk.BIP.SDE.gillespie-pysrc.html#Model">source&nbsp;code</a></span></p>
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          <td><span class="summary-sig"><a href="trunk.BIP.SDE.gillespie.Model-class.html#__init__" class="summary-sig-name">__init__</a>(<span class="summary-sig-arg">self</span>,
        <span class="summary-sig-arg">vnames</span>,
        <span class="summary-sig-arg">rates</span>,
        <span class="summary-sig-arg">inits</span>,
        <span class="summary-sig-arg">tmat</span>,
        <span class="summary-sig-arg">propensity</span>)</span><br />
      Class representing a Stochastic Differential equation.</td>
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            <span class="codelink"><a href="trunk.BIP.SDE.gillespie-pysrc.html#Model.__init__">source&nbsp;code</a></span>
            
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          <td><span class="summary-sig"><a name="getStats"></a><span class="summary-sig-name">getStats</span>(<span class="summary-sig-arg">self</span>)</span></td>
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            <span class="codelink"><a href="trunk.BIP.SDE.gillespie-pysrc.html#Model.getStats">source&nbsp;code</a></span>
            
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          <td><span class="summary-sig"><a href="trunk.BIP.SDE.gillespie.Model-class.html#run" class="summary-sig-name">run</a>(<span class="summary-sig-arg">self</span>,
        <span class="summary-sig-arg">method</span>=<span class="summary-sig-default">'SSA'</span>,
        <span class="summary-sig-arg">tmax</span>=<span class="summary-sig-default">10</span>,
        <span class="summary-sig-arg">reps</span>=<span class="summary-sig-default">1</span>,
        <span class="summary-sig-arg">viz</span>=<span class="summary-sig-default">False</span>,
        <span class="summary-sig-arg">serial</span>=<span class="summary-sig-default">False</span>)</span><br />
      Runs the model.</td>
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          <td><span class="summary-sig"><a name="GSSA"></a><span class="summary-sig-name">GSSA</span>(<span class="summary-sig-arg">self</span>)</span><br />
      Gillespie Direct algorithm</td>
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            <span class="codelink"><a href="trunk.BIP.SDE.gillespie-pysrc.html#Model.GSSA">source&nbsp;code</a></span>
            
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<a name="__init__"></a>
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  <h3 class="epydoc"><span class="sig"><span class="sig-name">__init__</span>(<span class="sig-arg">self</span>,
        <span class="sig-arg">vnames</span>,
        <span class="sig-arg">rates</span>,
        <span class="sig-arg">inits</span>,
        <span class="sig-arg">tmat</span>,
        <span class="sig-arg">propensity</span>)</span>
    <br /><em class="fname">(Constructor)</em>
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  </td><td align="right" valign="top"
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  Class representing a Stochastic Differential equation.
  <dl class="fields">
    <dt>Parameters:</dt>
    <dd><ul class="nomargin-top">
        <li><strong class="pname"><code>vnames</code></strong> - : list of strings</li>
        <li><strong class="pname"><code>rates</code></strong> - : list of fixed rate parameters</li>
        <li><strong class="pname"><code>inits</code></strong> - : list of initial values of variables. Must be integers</li>
        <li><strong class="pname"><code>tmat</code></strong> - : Transition matrix; numpy array with shape=(len(inits),len(propensity))</li>
        <li><strong class="pname"><code>propensity</code></strong> - : list of lambda functions of the form: lambda r,ini: some function of rates ans inits.</li>
    </ul></dd>
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  <h3 class="epydoc"><span class="sig"><span class="sig-name">run</span>(<span class="sig-arg">self</span>,
        <span class="sig-arg">method</span>=<span class="sig-default">'SSA'</span>,
        <span class="sig-arg">tmax</span>=<span class="sig-default">10</span>,
        <span class="sig-arg">reps</span>=<span class="sig-default">1</span>,
        <span class="sig-arg">viz</span>=<span class="sig-default">False</span>,
        <span class="sig-arg">serial</span>=<span class="sig-default">False</span>)</span>
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  Runs the model.
  <dl class="fields">
    <dt>Parameters:</dt>
    <dd><ul class="nomargin-top">
        <li><strong class="pname"><code>method</code></strong> - : String specifying the solving algorithm. Currently only 'SSA'</li>
        <li><strong class="pname"><code>tmax</code></strong> - : duration of the simulation.</li>
        <li><strong class="pname"><code>reps</code></strong> - : Number of replicates.</li>
        <li><strong class="pname"><code>viz</code></strong> - : Boolean. Whether to show graph of each replicate during simulation</li>
        <li><strong class="pname"><code>serial</code></strong> - : Boolean. False to run replicate in parallel when more than one core is a vailable. True to run them serially (easier to debug).</li>
    </ul></dd>
    <dt>Returns:</dt>
        <dd>a numpy array of shape (reps,tmax,nvars)</dd>
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